title: Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends.
abstract: OBJECTIVE
  Obesity prevalence in the United States appears to be leveling, but the reasons behind the plateau remain unknown. Mechanistic insights can be provided from a mathematical model. The objective of this study is to model known multiple population parameters associated with changes in body mass index (BMI) classes and to establish conditions under which obesity prevalence will plateau.
  
  
  METHODS
  A differential equation system was developed that predicts population-wide obesity prevalence trends. The model considers both social and nonsocial influences on weight gain, incorporates other known parameters affecting obesity trends, and allows for country specific population growth.
  
  
  RESULTS
  The dynamic model predicts that: obesity prevalence is a function of birthrate and the probability of being born in an obesogenic environment; obesity prevalence will plateau independent of current prevention strategies; and the US prevalence of overweight, obesity, and extreme obesity will plateau by about 2030 at 28%, 32%, and 9% respectively.
  
  
  CONCLUSIONS
  The US prevalence of obesity is stabilizing and will plateau, independent of current preventative strategies. This trend has important implications in accurately evaluating the impact of various anti-obesity strategies aimed at reducing obesity prevalence.
authors.affiliation: Center for Quantitative Obesity Research, Montclair State University, Montclair, New Jersey, USA.
authors.forename: Diana M
authors.initials: DM
authors.lastname: Thomas
authors.forename: Marion
authors.initials: M
authors.lastname: Weedermann
authors.forename: Bernard F
authors.initials: BF
authors.lastname: Fuemmeler
authors.forename: Corby K
authors.initials: CK
authors.lastname: Martin
authors.forename: Nikhil V
authors.initials: NV
authors.lastname: Dhurandhar
authors.forename: Carl
authors.initials: C
authors.lastname: Bredlau
authors.forename: Steven B
authors.initials: SB
authors.lastname: Heymsfield
authors.forename: Eric
authors.initials: E
authors.lastname: Ravussin
authors.forename: Claude
authors.initials: C
authors.lastname: Bouchard
mesh_terms: D000465:Algorithms; D001723:Birth Rate; D015992:Body Mass Index; D019049:Developed Countries; D006293:Health Promotion; D019456:Health Transition; D006801:Humans; D008954:Models, Biological; D018673:Nutrition Policy; D009765:Obesity / Q000175:diagnosis / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control; D009767:Obesity, Morbid / Q000175:diagnosis / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control; D050177:Overweight / Q000175:diagnosis / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control; D015995:Prevalence; D006113:United Kingdom / Q000453:epidemiology; D014481:United States / Q000453:epidemiology; D015430:Weight Gain